Big data refers to the aggressive growth and accessibility of structured (traditional numeric data) and unstructured data (modern social media, internet,) which allows for better business analysis. Listed below are the three ‘Vs’ of big data definition as ascribed by Douglas Laney, pioneer of Data warehousing and the field Infonomics.
- Volume: the amount of data whether relevant or irrelevant being collected, stored and analyzed by industries
- Velocity: how fast people can get access to available data
- Variety: the various formats in which data is presented
Because big data may exceed processing capacities of conventional systems, analysis is important to help companies reap benefits from the data, there needs to be a processing procedure. So companies must seek cost effect approaches to manage and regulate the incoming information so it translates into benefit. While some big box companies have had access to the benefits of big data, it used to be at a phenomenal cost; however, with cloud architectures and open source software such as Hadoop, and MapReduce, companies with fewer resources can extract value at a lesser expense.
Big Data Analytics
The process of gathering, organizing and analyzing large volumes of information for customer patterns and useful content is called “analytics”. This process provides steps to analyze and use information garnered from big data so companies can improve sales, boost efficiency and improve operations and customer experience. Because of the differences in volume, format and ways in which data can be gathered, processed and implemented, the task of performing beneficial analytics can be daunting. But with the help of specialized software tools that help with data mining, forecasting and optimization along with other key elements, companies can achieve high performance data analytics to help reach their goals.
Therefore a thorough review of the data warehoused in companies will aid with sound decision making, problem solving and future growth.
Business intelligence systems can also be utilized to cross analyze large amounts of data and provide past, present and future views of business practices. So employing big data analysis through business intelligence practices is paramount to success.